Blood pressure measurement and the prevalence of postprandial hypotension

Background: Postprandial hypotension (PPH) is a serious condition that has been shown to be an independent risk factor for falls, fractures and death. Purpose: The prevalence of this problem in older adults with a past history of falls has shown a wide variability in the literature; the present study seeks to examine how the frequency with which blood pressure is measured impacts the prevalence and severity of PPH. Methods: Older adults were recruited sequentially from a geriatric medicine falls clinic for meal testing (n=95). All subjects (mean age 77.5±0.7 years, 61±5% female) were fasting prior to each 90 min standardized meal test. A Finometer (Finapres Medical Systems BV) was used to monitor blood pressure. Beat-by-beat systolic (SBP) measures were averaged for 0.5, 1, 2, 3, 5, 6, 9, 10, 15, 18, 30, 45 and 90 min respectively during the meal test. Results: Using the original diagnostic method of checking mean blood pressure every 10 min resulted in a PPH prevalence of 42.1±5.1% in our population, with an overall range from 81.1±4.0% to 11.6±3.3% depending on the frequency of calculating SBP. The maximal observed postprandial decrease in SBP also showed a significant difference with blood pressure measurement frequency (

Combining GLP-1 Receptor Agonists and Basal Insulin in Older Adults with Type 2 Diabetes: Focus on Lixisenatide and Insulin Glargine

Abstract: Estimates suggest that there are currently 122.8 million adults 65–99 years of age living with diabetes, of whom 90–95% are diagnosed with type 2 diabetes (T2D). Over the past two decades, a greater understanding of the complex and multifactorial pathogenesis of T2D has resulted in the development and introduction of new-generation classes of glucose-lowering therapies, which are now extensively endorsed by prevailing guidelines and are increasingly being used worldwide. These newer agents may further assist in the effective pharmacological management of T2D through the provision of patient-centered care that acknowledges multimorbidity and is respectful of and responsive to individual patient preferences and barriers. Given these considerations, the therapeutic approach in older patients with T2D is complex, particularly in those who have functional dependence, frailty, dementia, or who are at end-of-life. It is currently too early to draw conclusions on the long-term use of newer glucose-lowering agents in this population, as their efficacy and safety in older adults remains largely unknown. In this review, we will discuss considerations for the use of glucose-lowering treatments in older adults, with particular focus on the use of basal insulin and glucagon-like peptide-1 receptor agonists, and the rationale for the use of combination therapy comprising these agents. Finally, we will review clinical data from studies of the fixed-ratio combination of insulin glargine and lixisenatide in older patients with T2D. Funding: Sanofi US, Inc

Correction to: Combining GLP-1 Receptor Agonists and Basal Insulin in Older Adults with Type 2 Diabetes: Focus on Lixisenatide and Insulin Glargine (Advances in Therapy, (2019), 36, 12, (3321-3339), 10.1007/s12325-019-01126-x)

On page 3331 of the original article, the word, ‘‘/LYXUMIA’’ has been removed from the section RATIONALE FOR COMBINATION THERAPY COMPRISING GLP-1 RAs AND BASAL INSULIN and the associated reference, numbered 100, has been corrected to: Xultophy® (insulin degludec/liraglutide) [summary of product characteristics]. Bagsvaerd, Denmark: Novo Nordisk A/S https://www.ema.europa.eu/ en/documents/product-information/xultophyepar- product-information_en.pdf. Accessed November 2019

Machine Learning Decision Support for Detecting Lipohypertrophy With Bedside Ultrasound: Proof-of-Concept Study

BackgroundThe most common dermatological complication of insulin therapy is lipohypertrophy. ObjectiveAs a proof of concept, we built and tested an automated model using a convolutional neural network (CNN) to detect the presence of lipohypertrophy in ultrasound images. MethodsUltrasound images were obtained in a blinded fashion using a portable GE LOGIQ e machine with an L8-18I-D probe (5-18 MHz; GE Healthcare). The data were split into train, validation, and test splits of 70%, 15%, and 15%, respectively. Given the small size of the data set, image augmentation techniques were used to expand the size of the training set and improve the model’s generalizability. To compare the performance of the different architectures, the team considered the accuracy and recall of the models when tested on our test set. ResultsThe DenseNet CNN architecture was found to have the highest accuracy (76%) and recall (76%) in detecting lipohypertrophy in ultrasound images compared to other CNN architectures. Additional work showed that the YOLOv5m object detection model could be used to help detect the approximate location of lipohypertrophy in ultrasound images identified as containing lipohypertrophy by the DenseNet CNN. ConclusionsWe were able to demonstrate the ability of machine learning approaches to automate the process of detecting and locating lipohypertrophy

The Extrapancreatic Effects of Glucagon-Like Peptide-1 and Related Peptides

Context: Glucagon-like peptide-1 (GLP-1) 7-36 amide, an insulinotropic hormone released from the intestinal L cells in response to nutrient ingestion, has been extensively reviewed with respect to β-cell function. However GLP-1 receptors are abundant in many other tissues. Thus, the function of GLP-1 is not limited to the islet cells, and it has regulatory actions on many other organs